Using hierarchical hidden Markov models to perform sequence-based classification of protein structure

International Conference on Signal Processing Proceedings, ICSP

Volumn , Issue , 2010, Pages 1789-1792

  Shi, Jian Yu ^a   Zhang, Yan Ning ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

Classification; Hidden Markov model; Hierarchical hidden Markov model; Protein sequence

Indexed keywords

CLASSIFICATION; EFFECTIVE TOOL; EXPERIMENTAL COMPARISON; EXPERIMENTAL METHODS; HIERARCHICAL HIDDEN MARKOV MODEL; HIERARCHICAL HIDDEN MARKOV MODELS; HIERARCHICAL STRUCTURES; MODEL PARAMETERS; PROTEIN SEQUENCE; PROTEIN SEQUENCES; PROTEIN STRUCTURES; SPATIAL STRUCTURE; STRUCTURAL CLASS;

OBJECT RECOGNITION; PROTEINS; SIGNAL PROCESSING;

HIDDEN MARKOV MODELS;

EID: 78651063979     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICOSP.2010.5656698     Document Type: Conference Paper

References (12)

1. A.D. Baxevanis, and B.F. Ouellette, "Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins," third ed., Wiley-InterScience, 2005.
2. C. Lampros, C. Papalukas, and T.P. Exarchos, Y. Goletsis, D.I. Fotiadis, "Sequence-based protein prediction using a reduced state-space hidden Markov model," Comput. Biol. Med., vol. 37,pp.1211-1224, 2007.
3. R. Hughey, and A. Krogh, "Hidden Markov models for sequence analysis: extension and analysis of the basic method," CABIOS, vol. 12 pp. 95-107, 1996.
4. S.R. Eddy, "Profile hidden Markov models," Bioinformatics, vol.14, pp.755-763,1998.
5. E. Lindahl, and A. Elofsson, "Identification of related proteins on family, superfamily and fold level," J. Mol. Biol., vol. 295, pp. 613-625, 2000.
6. S. Y.g Lee, J. Y. Lee, K. S. Jung, and K. H. Ryub. "A 9-state hidden Markov model using protein secondary structure information for protein fold recognition," Computers in Biology and Medicine,vol. 39, pp. 527- 534, 2009.
7. N.C. Jones, and P.A. Pevzener, "An Introduction to Bioinformatics Algorithms," The MIT Press, Cambridge, MA,2004.
8. P. Baldi, and S. Brunak, "Bioinformatics: The Machine Learning Approach," The MIT Press, Cambridge, MA, 2001.
9. W. Kabsch, and C. Sander, "Directory of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features," Biopolymers, vol. 22, pp. 2577-2637, 1983.
10. A.Andreeva, D.Howorth, J.-M. Chandonia, S.E. Brenner, T.J.P. Hubbard, C. Chothia, and A.G. Murzin (2007). "Data growth and its impact on the SCOP database: new developments," Nucl. Acids Res., vol. 36, pp.D419-D425, 2008.
11. S. Fine, Y.Singer, and N.Tishby: "The Hierarchical Hidden Markov Model: Analysis and Applications," Mach Learn, vol.32, pp.41-62, 1998.
12. C.H.Q. Ding, and I. Dubchak: "Multi-class protein fold recognition using support vector machines and neural networks," Bioinformatics, vol. 17, pp.349-358, 2001.